Suma Pranitha Konduru

Data Labeling Analyst | Data-driven Software Engineer
Buffalo, US.

About

Highly analytical and data-driven Software Engineer with 2+ years of experience, specializing in data labeling, quality assurance, and AI/ML techniques. Proven ability to act as a Subject Matter Expert, optimize complex workflows, and deliver actionable insights for product enhancement, aligning with Meta's Data Labeling Analyst objectives. Excels in critical analysis, strategic organization, and cross-functional communication to drive operational excellence and improve data quality in ambiguous environments.

Work

University at Buffalo
|

Research Assistant

Buffalo, New York, US

Summary

Led the implementation and optimization of data labeling and quality-control pipelines to ensure reliable input for advanced NLP and LLM research.

Highlights

Spearheaded the implementation of data labeling and quality-control pipelines, ensuring high-fidelity input crucial for cutting-edge NLP and LLM research initiatives.

Conducted rigorous quality audits and generated comprehensive labeling metrics, transforming data into actionable insights that significantly improved operational KPIs.

Served as a Subject Matter Expert for intricate labeling workflows, developing clear reproducibility guides and comprehensive workflow documentation.

Collaborated effectively with cross-functional teams to resolve tooling issues and integrate approved workflow updates, enhancing overall operational efficiency.

Contriver
|

Software Engineer

Buffalo, New York, US

Summary

Developed robust backend systems and optimized data processing workflows to enable real-time collaborative labeling and analytics for product teams.

Highlights

Engineered REST APIs and microservices for scalable structured data ingestion and transformation, facilitating real-time collaborative labeling and analytics.

Cultivated strong vendor relationships, participating in weekly business reviews to proactively resolve quality and technical barriers.

Identified and implemented process optimizations that successfully reduced data-retrieval latency by 20%, significantly enhancing system efficiency.

Leveraged Excel, SQL, and Python for in-depth analysis of large datasets, delivering data-driven dashboards to inform strategic decisions.

Contriver
|

Software Engineer Intern

Buffalo, New York, US

Summary

Contributed to the development of a collaborative code editor, focusing on backend logic for real-time data synchronization and scalable architecture.

Highlights

Developed backend logic for a collaborative code editor, implementing real-time data synchronization and version tracking functionalities.

Applied object-oriented principles and modular architecture to build scalable data workflows, enhancing system adaptability and maintainability.

Diagnosed and resolved root causes of latency issues within a distributed editing environment, significantly improving system performance.

Education

University at Buffalo, The State University of New York
Buffalo, New York, United States of America

Master of Science

Computer Science and Engineering

Certificates

AWS Certified Developer - Associate

Issued By

AWS

Machine Learning with Python

Issued By

Verzeo

Full Stack Developer

Issued By

GeeksforGeeks

IBM CLOUD ESSENTIALS

Issued By

IBM

AI for Beginners

Issued By

HP LIFE

Introduction to Generative AI

Issued By

Google

Skills

Programming Languages

Java, Python, C++, JavaScript, SQL.

Frameworks/Tools

React, Redux, Flask, Docker, Jenkins, Git, Airflow, VS Code, Power BI, Excel.

Cloud & AI/ML Technologies

AI, ML, LLM, DL, CNN, NLP, Computer Vision, AWS, GCP, Azure, CI/CD, Kubernetes.

Data & Big Data

Hadoop, Big Query, Spark, ETL/ELT, Kafka, EventHub, MySQL, PostgreSQL, MongoDB, NoSQL.

Concepts & Methodologies

Data Engineering, ETL Pipelines, Distributed Systems, Scalability, Latency Optimization, Agile, Critical Analysis, Strategic Planning, Stakeholder Management, Communication, Problem Solving, Quality Assurance, Workflow Optimization.

Projects

License Plate Detection with Privacy Enhancement

Summary

Designed and implemented a real-time, privacy-enhanced license plate detection system, featuring a distributed ETL pipeline for image data processing and optimized workload scheduling.

American Sign Language Detection using Deep Neural Networks

Summary

Constructed a real-time ASL recognition system utilizing deep neural networks, deployed on AWS cloud infrastructure for scalable, sub-second translation for live users.